• INITIAL PARAMETERS ANALYSIS FOR MIXTURE OF GAUSSIAN MODEL

LIHONG WANG*, SHANLIN WANG, RUIMIN WU

Abstract

The mixture of Gaussian is a common model for background subtraction. There are several parameters in such a model. Obviously, the assignment of initial values to these parameters affects the accuracy of background subtraction. In this paper, we analyze in detail the impact of different initial parameter values based on the EM algorithm. The tested results of waving trees video sequences have illustrated. This parameter values analysis provides suggestions how to choose suitable initial parameter values while using a mixture of Gaussian model in video surveillance application